This report contains a descriptive analysis of fisheries in Roatan, based on the sampled, time-series database of fish landings collected by CORAL and its partners.
# ==== Data preparation ====
# Preparing columns
dat <- dat |>
# Filtering data for only Roatan
filter(zona == 'Roatan') |>
# Using the cleaned common names as default
mutate(nc_og = nombre_comun) |>
mutate(nombre_comun = str_to_title(nombre_comun_cln)) |>
# Adding "sp" to columns where the genus is present but no species is present
mutate(species = if_else((is.na(species) & !is.na(genus)), 'sp', species)) |>
tidyr::unite(nombre_cientifico, genus, species, sep=' ', remove=F, na.rm=T) |>
# Factorizing relevant columns
mutate(comunidad = as.factor(comunidad)) |>
mutate(zona_pesca = as.factor(zona_pesca)) |>
# Getting year, month, and year-month columns
mutate(year = year(fecha), month=month(fecha), .after='fecha') |>
mutate(ym = paste(year, str_pad(month, 2, 'left', '0'), sep='-'), .after=month) |>
mutate(month = month.abb[month]) |>
# Factorizing year and month column
mutate(year = as.factor(year)) |>
mutate(month = factor(month, levels=month.abb)) |>
# Converting weight to kg
mutate(peso = peso/1000)
# Removing rows where no date is given
dat <- dat |> filter(!is.na(fecha))
# Removing outliers (detected based on IQR ranges specific to each
# genus/family) - based on weight
dat <- dat |>
# A helper grouping variable that uses the family name if the scientific name
# is not available
mutate(taxa = if_else(is.na(nombre_cientifico), family, nombre_cientifico)) |>
group_by(taxa) |>
# Naming outliers for each taxa group
mutate(isoutlier = ifelse(all(is.na(peso)), 'No', anomalize::iqr(peso))) |>
ungroup()
# Separating those that are outliers for manual inspection - they don't look
# unreasonable, so not removing anything
outliers <- dat |> filter(isoutlier == "Yes")
# Cleaing outliers
dat <- dat |>
# Removing unreasonable weight rows
filter(peso < 34) |>
# filter(isoutlier == "No") |>
# Removing outlier related fields
select(-isoutlier, -taxa)
## 2. Most-used gears
## [1] "Diversided de especias capturadas por comunidad:"
## camp bay Comunidad diamond rock Punta Gorda Santa Elena Santa ELena
## 1.2813606 0.0000000 1.5427665 0.9088899 1.6983812 1.8067367
## SantaElena
## 2.0836379
## [1] "Diversidad de especias capturadas por tipo de arte:"
## Anzuelo Buceo Carrete Cuerda
## 2.0629805 0.7654211 0.8470101 1.0571363
## [1] "Diversidad de tipos de artes por comunidad:"
## camp bay Comunidad diamond rock Punta Gorda Santa Elena Santa ELena
## 0.0000000 0.0000000 0.0000000 0.6914161 0.5742527 0.2921467
## SantaElena
## 0.2835479
Maturity data were only gathered for a small subset of the total sampling effort. The observations which contain maturity data have the following characteristics:
## [1] "Total number of observations with maturity data: 151"
## [1] "Date range: 2021-01-08" "Date range: 2021-12-16"
## [1] "Number of maturity observations by species:"
##
## Lutjanus sp Ocyurus chrysurus Sphyraena sp Thunnus sp
## 56 27 15 40
## Xiphias gladius
## 13
## [1] "Distribution of maturity classes:"
##
## 3
## 151
## [1] "Distribution of sexes:"
## < table of extent 0 >
Since the only maturity class reported is “3” = “mature”, and no sexes are reported at all, no further analysis could be conducted for these data.